Metal material production process machinery is becoming larger due to the development of industry. Since there are many overseas manufacturers of large machines used in industrial fields, there are limitations in investigating the manufacturer's noise prediction method and measurement method. A noise map was prepared to obtain information necessary for noise reduction and to effectively manage noise companies. It was modeled with the drawings provided to prepare the noise map and the results of the actual measurement of the site. In order to improve the noise environment of workers, there was a noise reduction effect when a soundproof wall was installed between the noise source and the worker's workplace.

Assessment of noise exposed population is to check the environment noise level and social influence in order to reduce the risks such as annoyance and disturbance that are generated by environmental noise. Also, this method suggests the preferential noise abatement policy and action plan by accurately finding the area that the noise causes harmful effect to human health. Recently, a noise map, which can predict noise in comprehensive area, is used for the assessment of noise exposed population, breaking from the methods using existing measures. In particular, countermeasure for noise can be considered more effectively by using assessment methods of noise exposed population for specific noise level, area and building types which are the main input factors in noise maps. In this study, we propose noise prediction at traffic noise due to noise map.

The purpose of this study was to establish the noise characteristics of noise sources and the corresponding noise reduction measures during each manufacturing process closest to the workers in the metalworking factory. To this end, the noise generated in the manufacturing process of metal products was measured and analyzed, and the frequency characteristics of noise sources and the causes of noise were identified. The noise map was used to predict the noise reduction effect. Moreover, it is expected that this will ultimately contribute to the reduction of human risks caused by the noise of the civil environment around metalworking factories.

Assessment of noise exposed population is to check the environment noise level and social influence in order to reduce the risks such as annoyance and disturbance that are generated by environmental noise. Also, this method suggests the preferential noise abatement policy and action plan by accurately finding the area that the noise causes harmful effect to human health. Recently, a noise map, which can predict noise in comprehensive area, is used for the assessment of noise exposed population, breaking from the methods using existing measures. In particular, countermeasure for noise can be considered more effectively by using assessment methods of noise exposed population for specific noise level, area, and building types which are the main input factors in noise maps. In this study, we propose noise reduction ranking decision at ship construction and repair process due to noise map.

Assessment of noise exposed population is to check the environment noise level and social influence in order to reduce the risks such as annoyance and disturbance that are generated by environmental noise. Also, this method suggests the preferential noise abatement policy and action plan by accurately finding the area that the noise causes harmful effect to human health. Recently, a noise map, which can predict noise in comprehensive area, is used for the assessment of noise exposed population, breaking from the methods using existing measures. In particular, countermeasure for noise can be considered more effectively by using assessment methods of noise exposed population for specific noise level, area, and building types which are the main input factors in noise maps. In this study, we propose noise reduction ranking decision at manufacturing process of metal material products due to noise map.

The object of this paper is investigate noise source at metal material product manufacturing plant and create noise map for predict noise. The plant is located close to a residential area, and residents noise exposure damage expected. Through this research 68 points noise sources were measured. And according to analysis result, 30 percent of noise sources are measured above 90dB(A). Based on this measurement results were create a noise map, and comparison between the predicted noise and the background noise. The noise maps were calculated by noise prediction software using measurement data, GIS data, ESRI SHP files and actual survey data. As a analysis result, metal material products manufacturing plants are will have an effect by noise on the nearby residential area.

This research helps you understand the road traffic noise levels by using a noise map. We have observed the change of the road traffic noise levels around 07:00～08:30 and 22:00～23:00 using the noise map in the city. The road traffic noise level is very high both at noon and at night around a beltway and an interchange that is linked with a highway. It seems that the main route of so many vehicles, which are at neighboring cities such as N city and D and H districts and which avoid traffic jams in the city, is the beltway and interchange. The road traffic noise level of a nearby express bus terminal, railroad station, and airport is more than 75 dB at noon and 65 dB at night. The road traffic noise level of G city at night is observed to be more than 55 dB. The noise levels of a residence area and a university are higher than a road with high noise levels when the commuters drive to work. The end of the day exceeds 11 o'clock because of a culture level of development that arouses spare time, eating out, adults' drinking culture, nightlife of the youth, etc. Therefore, the road traffic noise level is high during late night hours, and it exceeds regulatory guidelines (55 dB(A)). It also damages the residence area that is located near the road.